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The detection of possible changes in extreme climate events, in terms of the frequency, intensity as well as duration assumes profound importance on the local, regional, and national scales, due to the associated critical socioeconomic consequences. Therefore, an attempt ismade in this paper to evaluate various aspects of future projections of precipitation extremes over India, as projected by a state-of-art regional climatemodeling system, known as PRECIS (Providing REgional Climates for Impacts Studies) towards the end of the 21st century (that is, 2071-2100) using standardized indices. Study reveals that PRECIS simulations under scenarios of increasing greenhouse gas concentration and sulphate aerosols indicate marked increase in precipitation towards the end of the 21st century and is expected to increase throughout the year. However the changes in daily precipitation and the precipitation extremes during summer monsoon (June through September) season are prominent than during the rest of year. PRECIS simulations under both A2 and B2 scenarios indicate increase in frequency of heavy precipitation events and also enhancement in their intensity towards the end of the 21st century. Both A2 and B2 scenarios show similar patterns of projected changes in the precipitation extremes towards the end of the 21st century. However, the magnitudes of changes in B2 scenario are on the lower side. [ABSTRACT FROM AUTHOR]

This study analyzed the long-term memory (LTM) in precipitation over Bénin synoptic stations from 1951 to 2010 using the detrended fluctuation analysis (DFA) method. Results reveal the existence of positive long-term memory characteristic in rainfall field. DFA exponent values are different regarding the concerned synoptic stations, reflecting the effect of geographical position and climate on the LTM. These values were related to the type of climate. The best DFA1-4 method depends on the geographical position of the studied station. However, DFA2 is generally the best in terms of spatial average from DFA1 to DFA4. In Bénin synoptic stations, except the Parakou station, the long-term temporal correlations are systematically the source of multifractality in rainfall. Except Natitingou, the strength of long-term memory characteristic decreases each twenty years in the study period. Considering the fractal approach, our results show that the subperiod 1991–2010 is not really a transition period as shown before. Thus, the drought is prolonging until 2010. So, fractal theory reveals more Bénin climatic characteristics. [ABSTRACT FROM AUTHOR]

A selected number of global climate models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) were evaluated over the Volta Basin for precipitation. Biases in models were computed by taking the differences between the averages over the period (1950–2004) of the models and the observation, normalized by the average of the observed for the annual and seasonal timescales. The Community Earth System Model, version 1-Biogeochemistry (CESM1-BGC), the Community Climate System Model Version 4 (CCSM4), the Max Planck Institute Earth System Model, Medium Range (MPI-ESM-MR), the Norwegian Earth System Model (NorESM1-M), and the multimodel ensemble mean were able to simulate the observed climatological mean of the annual total precipitation well (average biases of 1.9% to 7.5%) and hence were selected for the seasonal and monthly timescales. Overall, all the models (CESM1-BGC, CCSM4, MPI-ESM-MR, and NorESM1-M) scored relatively low for correlation (<0.5) but simulated the observed temporal variability differently ranging from 1.0 to 3.0 for the seasonal total. For the annual cycle of the monthly total, the CESM1-BGC, the MPI-ESM-MR, and the NorESM1-M were able to simulate the peak of the observed rainy season well in the Soudano-Sahel, the Sahel, and the entire basin, respectively, while all the models had difficulty in simulating the bimodal pattern of the Guinea Coast. The ensemble mean shows high performance compared to the individual models in various timescales. [ABSTRACT FROM AUTHOR]